1. Field of the Invention
The present invention relates to an object recognition apparatus, and more particularly to a pattern recognition apparatus which segmentally approximates a pattern derived from an image data of an outline of an object region to recognize the pattern.
2. Description of the Prior Art
One of prior art, object recognition apparatus which have been put into practice classifies an object region into groups of same density pixels based on binary images of the object and recognizes the object based on external shape characteristics such as an area of the region, a center of gravity, a maximum dimension from the center of gravity, a minimum dimension from the center of gravity and a peripheral length.
Such an apparatus is effective to recognize the object when characteristics which are significantly different among the objects to be recognized can be selectively used, and can attain a high speed recognition. However, when objects such as keys which are different in a limited portion of the shape and identical in most portions of the shape are to be recognized, it is difficult to find out characteristics which allow effective classification of those objects or it is necessary to combine many characteristics to recognize the objects. Accordingly, the above apparatus is not effective to recognize similar objects.
On the other hand, in a pattern matching method, a partial pattern (for example, a 12.times.12 pixel pattern) of an object pixel pattern which most appropriately represents a characteristic of the object is stored as a dictionary pattern, and the dictionary pattern is superimposed on an input image and it is shifted pixel by pixel to find out an optimal matching position to recognize the object.
Since this method examines the degree of matching by superimposing the pattern, it is strong against a small noise and has a sufficient recognition ability to analogous patterns. However, the object to be recognized must have the same attitude as that of the previously stored dictionary pattern and hence this method cannot recognize an object with an arbitrary rotation.
One approach to resolve the above problem is a polar coordinates matching method. In this method, a center of gravity of an object region is determined, a pattern of a region boundary of the object is represented by a polar curve (r-.theta.) with an origin of the polar coordinate being at the center of gravity and it is superimposed on a predetermined dictionary (r-.theta.) curve and it is rotated slightly at a time to find out a most matching position.
This method can recognize an object of an arbitrary rotation, but since the preparation of the r-.theta. curve needs much processing, the amount of processing increases when a high precision recognition of analogous objects is required.